Enterprise Architect
Job in
560001, Vasanthanagar, Karnataka, India
Listed on 2026-09-01
Listing for:
EXL
Full Time
position Listed on 2026-09-01
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below
Job Description:
Experience : 8-15 years
Location :
Bangalore
This overarching role combines deep technical mechanics, full-stack application design, and robust security governance to lead the enterprise AI strategy. AVP, GenAI Enterprise Architect
Experience:
8–15 Years
Role Overview :
Design and deploy enterprise-grade AI solutions (LLMs, RAG, agents) by selecting appropriate models, building data pipelines, and integrating them with cloud platforms (AWS, Azure, GCP). Lead technical strategies, ensure scalability, manage AI security/ hallucinations, and bridge business needs with engineering teams.
Key Responsibilities • • • •
• System Design & Architecture:
Architect end-to-end Generative AI systems, including retrieval-augmented generation (RAG) and vector data systems. Model Selection & Tuning:
Evaluate and select cutting-edge commercial (e.g., GPT-4) and open-source models, and fine-tune models for domain-specific use cases. LLMOps & Pipelines:
Establish LLMOps standards for model versioning, evaluation, prompt management, and CI/CD, ensuring robust, production-grade AI. Integration & Security:
Integrate AI solutions with existing APIs, applications, and databases while enforcing security, privacy, and guardrails to manage hallucinations and adversarial attacks. Strategic Leadership:
Collaborate with stakeholders to map business challenges to AI solutions and establish AI governance frameworks.
Required
Skills & Qualifications • •
•
• Technical Expertise:
Deep knowledge of NLP, Python, deep learning frameworks (PyTorch/ Tensor Flow), and AI frameworks like Lang Chain, Autogen, or CrewAI. Cloud & Data Systems:
Extensive hands-on experience with AI services on AWS, Azure, or GCP. Expertise in vector databases (e.g., Pinecone, Milvus, Chroma) and embedding techniques. GenAI-Specific
Skills:
Prompt engineering, RAG architectures, Fine-tuning LLMs, Vector databases.
Soft Skills:
Problem-solving mindset, strategic thinking, and strong communication (explaining AI to non-technical teams).
•
Qualifications:
Bachelor’s / Master’s in Computer Science, AI, Data Science, or related field; 8–15 years in software engineering, ML, or AI roles.
Experience with enterprise-level systems
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